Benefits of resource-based stemming in hungarian information retrieval

Authors:
Péter Halácsy;Viktor Trón
Affiliations:
Budapest University of Technology and Economics, Centre for Media Research;International Graduate College, Saarland University and University of Edinburgh
Venue:
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
Year:
2006

Citing 4
Cited 3

Hunmorph: open source word analysis

Software '05 Proceedings of the Workshop on Software
Web-based frequency dictionaries for medium density languages

WAC '06 Proceedings of the 2nd International Workshop on Web as Corpus
Monolingual, bilingual, and GIRT information retrieval at CLEF-2005

CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
Exploring new languages with HAIRCUT at CLEF 2005

CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories

Web-Based Lemmatisation of Named Entities

TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
Effect of Preprocessing on Extractive Summarization with Maximal Frequent Sequences

MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Improved recognition of spontaneous Hungarian speech: morphological and acoustic modeling techniques for a less resourced task

IEEE Transactions on Audio, Speech, and Language Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper discusses the impact of resource-driven stemming in information retrieval tasks. We conducted experiments in order to identify the relative benefit of various stemming strategies in a language with highly complex morphology. The results reveal the importance of various aspects of stemming in enhancing system performance in the IR task of the CLEF ad-hoc monolingual Hungarian track.